ChIMES Carbon 2.0: A transferable machine-learned interatomic model harnessing multifidelity training data
Sign Up to like & getrecommendations! Published in 2025 at "npj Computational Materials"
DOI: 10.1038/s41524-024-01497-y
Abstract: We present new parameterizations of the ChIMES physics informed machine-learned interatomic model for simulating carbon under conditions ranging from 300 K and 0 GPa to 10,000 K and 100 GPa, along with a new multi-fidelity… read more here.
Keywords: learned interatomic; chimes carbon; interatomic model; model ... See more keywords
Accelerating the training and improving the reliability of machine-learned interatomic potentials for strongly anharmonic materials through active learning
Sign Up to like & getrecommendations! Published in 2025 at "Physical Review Materials"
DOI: 10.1103/physrevmaterials.9.063801
Abstract: Molecular dynamics (MD) employing machine-learned interatomic potentials (MLIPs) serve as an efficient, urgently needed complement to molecular dynamics. By training these potentials on data generated from methods, their averaged predictions can exhibit comparable performance to… read more here.
Keywords: anharmonic materials; learned interatomic; interatomic potentials; active learning ... See more keywords